Author here. Our main focus right now is on vibration and non-voice audio. For vibration we use spectral analysis through butterworth filters, FFT over the resu

Author here. Our main focus right now is on vibration and non-voice audio. For vibration we use spectral analysis through butterworth filters, FFT over the result, looking at the peaks and locations of the FFT result, and then at spectral power buckets. For audio we look at MFCC (sometimes paired with a bandpass filter). The source for these are in https://github.com/edgeimpulse/processing-blocks https://github.com/edgeimpulse/processing-blocks (Python) and https://github.com/edgeimpulse/inferencing-sdk-cpp https://github.com/edgeimpulse/inferencing-sdk-cpp (optimised C++). What’s though on our end is that we need to run the DSP in real-time on very constrained devices. Unfortunately I have very little good resources on learning more. I’ve done lots of experimentation in Matlab, just getting raw sensor data and playing with the signal processing toolkit that they sell.